Fault Detection for the Scraper Chain Based on Vibration Analysis Using the Adaptive Optimal Kernel Time-Frequency Representation
Joint Authors
Yang, Shanguo
Zhu, Zhencai
Wei, Li
Zhang, Xing
Jiang, Fan
Source
Issue
Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-14, 14 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2019-07-24
Country of Publication
Egypt
No. of Pages
14
Main Subjects
Abstract EN
A scraper conveyor is a key component of large-scale mechanized coal mining equipment, and its failure patterns are mainly caused by chain jam and chain fracture.
Due to the difficulties with direct measurement for multiple performance parameters of the scraper chain, this paper deals with a novel strategy for fault detection of the scraper chain based on vibration analysis of the chute.
First, a chute vibration model (CVM) is applied for modal analysis, and the hammer impact test (HIT) is conducted to validate the accuracy of the CVM; second, the measuring points for vibration analysis of the chute are determined based on the modal assurance criterion (MAC); and third, to simulate the actual vibration properties of the chute, a dynamic transmission system model (DTSM) is constructed based on finite element modeling.
The fixed-point experimental testing (FPET) is then conducted to indicate the correctness of simulation results.
Subsequently, the DTSM-based vibration responses of the chute under different operating conditions are obtained.
In this paper, the proposed strategy is employed to determine the occurrence of chain faults by amplitude comparisons, while failure patterns are distinguished by the adaptive optimal kernel time-frequency representation (AOKR).
American Psychological Association (APA)
Zhang, Xing& Wei, Li& Zhu, Zhencai& Yang, Shanguo& Jiang, Fan. 2019. Fault Detection for the Scraper Chain Based on Vibration Analysis Using the Adaptive Optimal Kernel Time-Frequency Representation. Shock and Vibration،Vol. 2019, no. 2019, pp.1-14.
https://search.emarefa.net/detail/BIM-1211466
Modern Language Association (MLA)
Zhang, Xing…[et al.]. Fault Detection for the Scraper Chain Based on Vibration Analysis Using the Adaptive Optimal Kernel Time-Frequency Representation. Shock and Vibration No. 2019 (2019), pp.1-14.
https://search.emarefa.net/detail/BIM-1211466
American Medical Association (AMA)
Zhang, Xing& Wei, Li& Zhu, Zhencai& Yang, Shanguo& Jiang, Fan. Fault Detection for the Scraper Chain Based on Vibration Analysis Using the Adaptive Optimal Kernel Time-Frequency Representation. Shock and Vibration. 2019. Vol. 2019, no. 2019, pp.1-14.
https://search.emarefa.net/detail/BIM-1211466
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1211466